Papers by Manh-Cuong Phan

2 papers
Metamo: Empowering Large Language Models with Psychological Distortion Detection for Cognition-aware Coaching (2025.emnlp-demos)

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Challenge: Metamo is a browser-based dialogue system that transforms an off-the-shelf large language model into an empathetic coach for everyday workplace concerns.
Approach: They propose a browser-based dialogue system that first identifies the cognitive distortion behind an emotion, then recognizes the user’s emotion, and finally produces a question-centered reply that invites reflection.
Outcome: Empirical tests on public corpora showed that the proposed system improved emotionrecognition quality and response diversity without sacrificing latency.
CMTD: Cognitive Modeling with Traits and Distortions for Multimodal Emotion Recognition in Conversations (2026.findings-acl)

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Challenge: Experimental results show that traits temper negativity bias from distortions, and cognitive modeling with psychological, visual, and acoustic information can improve the performance of MERC.
Approach: They propose a framework for multimodal emotion recognition in conversations that takes advantage of stable personality traits, dynamic cognitive distortions, visual and acoustic features of interlocutors to enhance the emotional intelligence of LLMs.
Outcome: Experimental results show that traits temper negativity bias from distortions, and cognitive modeling with psychological, visual, and acoustic information can improve the performance of MERC.

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